Recommendation and personalization related systems exist in the academic world as well as commercial services. There are two major schools, collaborative filtering, where recommendations for a user are given based on the behavior of other users that are considered “similar” to a target user and content based filtering, where recommendations for a user are based on similarity of items the user likes to the items in the database. Most systems that are currently deployed make use of the collaborative filtering since it is difficult to create a meta database for all items, which is generally required to compute the similarity between content items. However, all systems of this kind are essentially server-based, which
a) requires a connection to the server, where client usage data is sent to and
b) requires a back connection to a client where the recommendations are sent.
However, for many systems, like e.g. television sets (TV sets) a bi-directional connection is typically not available.
It is an object of the present invention to recommend content items without needing a bi-directional connection.
The object is solved by a method, a system and a receiver according to the claims.
Further embodiments are defined in dependent claims.
Further details will become apparent from a consideration of the drawings and ensuing description.